As a cloud project owner, you want your environment to run smoothly and efficiently. At Google Cloud, one of the ways we help you do that is through a family of tools we call Recommenders, which leverage analytics and machine learning to automatically detect issues and present you with optimizations that you can act on.

When we graduated Loki into a GA release last year, there were more than 137 contributors who already made more than 1,000 contributions to the project. We also added hosted Loki to the lineup of Grafana Cloud offerings after it proved to be stable internally for our ops cluster, storing 40TB and half a trillion log lines each month. There was, however, one persistent problem that kept surfacing, especially for developers who were writing applications in Go: The regex package was slow.

Amazon Web Services Elastic Load Balancer (AWS ELB) enables websites and web services to serve more requests from users by adding more servers based on need. Unhealthy ELB can cause your website to go offline or slow down dramatically. Elastic Load Balancing automatically distributes incoming application traffic across multiple Amazon EC2 instances.

Netlify allows developers and businesses to publish modern web projects right from your git repos. There’s nothing to set up & no servers to maintain. This past month, Netlify launched Build Plugins, which allows Netlify users to automate and customize their build processes. We loved what the Netlify team was building and how they were automating tedious tasks for developers. So we built the Sentry Netlify Build Plugin!

I’d like to share some of the best practices we’ve learned on our journey to battle performance issues with the Jaeger tracing tool. Some may say we are experts in logging. We log for a living, and have our log analytics service (which we based on open source ELK Stack) to prove it. We’ve mastered logging to the level where debugging and troubleshooting our system is a no-brainer.